Assessing clustering methods for exploratory spatial data analysis
AbstractExploratory spatial data analysis continues to be an important area of research. The use and application of clustering methods for the analysis of spatially referenced data is beginning to show some promise. However, a variety of clustering methods does exist. It is essential that a better understanding of these approaches in the geographic domain be pursued in terms of data requirements, computational efficiencies and inherent biases. This paper presents an initial attempt to demonstrate strengths and weaknesses of various clustering approaches for exploratory spatial data analysis.
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Bibliographic InfoPaper provided by European Regional Science Association in its series ERSA conference papers with number ersa98p346.
Date of creation: Aug 1998
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